Abstract
The paper develops a neuromorphic system on a Spartan 6 field programmable gate array (FPGA) board to generate locomotion patterns (gaits) for three different legged robots (biped, quadruped, and hexapod). The neuromorphic system consists of a reconfigurable FPGA-based architecture for a 3G artificial neural network (spiking neural network), which acts as a Central Pattern Generator (CPG). The locomotion patterns, are then generated by the CPG through a general neural architecture, which parameters are offline estimated by means of grammatical evolution and Victor-Purpura distance-based fitness function. The neuromorphic system is fully validated on real biped, quadruped, and hexapod robots.
| Original language | English |
|---|---|
| Article number | 7909022 |
| Pages (from-to) | 8301-8312 |
| Number of pages | 12 |
| Journal | IEEE Access |
| Volume | 5 |
| DOIs | |
| Publication status | Published - 2017 |
| Externally published | Yes |
Keywords
- FPGA
- grammatical evolution
- legged robots
- neuromorphic engineering
- spiking neural networks
- Victor-Purpura distance
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